Abstract Alcoholic hepatitis (AH) is a leading cause of liver-related morbidity and mortality with a remarkable paucity of effective therapeutics. NIAAA has sponsored a number of RFAs to form the Alcoholic Hepatitis Network (AlcHepNet). Collectively, the network will synergize efforts and expertise to better understand AH and develop novel effective and safe therapies for severe AH. Because of the diversity of studies that will be proposed under these RFAs, two Data Coordinating Centers will be established to better support these studies efficiently and effectively to produce high quality reproducible research from each funded study. This application is for the Data Coordinating Center at the University of Massachusetts Medical School (DCC UMMS) for AlcHepNet which will provide the statistical and data management leadership to: (1) translational studies, (2) basic/pre-clinical studies, and (3) pilot clinical trials while using innovations based on previous experience to facilitate the operations of these studies with shorter timelines and greater quality. The DCC UMMS Team, housed in the Quantitative Methods Core (QMC) of the Department of Quantitative Health Sciences, is experienced in both NIH and FDA clinical trials and has implemented a number of proven, validated approaches in short timeframes and with minimal budgets with increased use of technology and monitoring tools. The Specific Aims of this proposal are: (1) Efficient and Effective Project Management - develop a robust infrastructure including communication support and administrative services to facilitate study objectives; (2) Rigorous Design and Analysis - provide high-level leadership in biostatistics and data management to the scientific methodology of the DCC UMMS supported studies; and (3) High Quality Study Implementation - ensure high quality of study results through a rigorous program of quality assurance and control, study monitoring, and DSMB and regulatory reporting. Each of these specific aims comprises a set of complex issues that determine efficiency and quality of implementation. Each will be addressed using multifaceted approaches that can address multiple issues at once. While there is a need for nimble response to changing needs across studies, there is also need for measured and documented approaches within the procedural/SOP framework of the DCC UMMS so that each approach is integrated within the DCC UMMS systems and contributes to higher quality, more reliable data and reproducible research.